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Data is the foundation on which businesses run their various operations. It’s essential, therefore, to ensure that this data is of high quality and cleansed of any impurities. SQL, or Structured Query Language, can be used in cleaning data, a process which is critical in improving data quality and in turn, decision-making processes within a business.
What is Data Cleansing?
Data cleansing, also known as data cleaning or data scrubbing, is the process of identifying and correcting or removing corrupt, inaccurate, or irrelevant parts of data in a database. Data in businesses is often derived from various sources, and inconsistencies are bound to occur. SQL provides functionalities to help in managing these inconsistencies.
Data Cleansing with SQL
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SQL, being a language designed for managing data in a relational database management system (RDBMS), contains various commands and functions that can be used for data cleansing.
Duplicates
Duplicate rows can be removed using SQL’s DISTINCT keyword. For instance, consider a table named ‘Employees’ with duplicate rows.
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SELECT DISTINCT * FROM Employees |
The DISTINCT keyword ensures that only unique rows are returned by the SELECT statement.
Null Values
Null values in a database often signify missing or unknown data. SQL provides the IS NULL and IS NOT NULL operators to check for null values. To find rows with null values in a column, use:
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SELECT * FROM Employees WHERE column_name IS NULL |
Replacing Nulls
You can replace null values with the SQL function COALESCE. It returns the first non-null value in a list.
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UPDATE Employees SET column_name = COALESCE(column_name, 'N/A') |
This statement will replace any null values in ‘column_name’ with ‘N/A’.
Inconsistent Data
Inconsistencies in data can be handled using SQL functions such as TRIM, UPPER, and LOWER. For instance, the TRIM function can be used to remove leading and trailing spaces from a string.
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UPDATE Employees SET column_name = TRIM(column_name) |
SQL’s flexibility and robustness make it a handy tool for data cleansing in ensuring data quality. With the right knowledge, a database administrator can ensure that their data is accurate, consistent, and usable.